# Author Shael Minuk
import pickle as pkl
import pandas as pd
sim_data = pd.read_pickle("sim_results.pkl")

sim_data["sub_thick"]=0
sim_data["sub_perm"]=0
## just changing the subtrate to map its thickness and permeativity, make it numerical and not categorical
sim_data.loc[(sim_data[9]=="Rogers RO3003"),"sub_thick"]=1.52e-3
sim_data.loc[(sim_data[9]=="Rogers RO3010"),"sub_thick"]=1.28e-3
sim_data.loc[(sim_data[9]=="Rogers RO3003"),"sub_perm"]=3
sim_data.loc[(sim_data[9]=="Rogers RO3010"),"sub_perm"]=10
sim_data=sim_data.drop([0,1,6,9],axis=1)
# one hot encode the categorical top mid bottom collumn :), now boolean 5_bot, 5_mid, 5_top etc etc instead of one col
sim_data=pd.get_dummies(sim_data,)
# store processed pickled data in model folder (dataframe)
sim_data.to_pickle("processed_data.pkl")




